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Proceedings Paper

Adversarial inferencing for generating dynamic adversary behavior
Author(s): Joshua M. Surman; Robert G. Hillman; Eugene Santos
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Paper Abstract

In the current world environment, the rapidly changing dynamics of organizational adversaries are increasing the difficulty for Military Analysts and Planners to accurately predict potential actions. As an integral part of the planning process, we need to assess our planning strategies against the range of potential adversarial actions. This dynamic world environment has established a necessity to develop tools to assist in establishing hypotheses for future adversary actions. Our research investigated the feasibility to utilize an adversarial tool as the core element within a predictive simulation to establish emergent adversarial behavior. It is our desire to use this intelligent adversary to generate alternative futures in performing Course of Action (COA) analysis. Such a system will allow planners to gauge and evaluate the effectiveness of alternative plans under varying actions and reactions. This research focuses on one of many possible techniques required to address the technical challenge of generating intelligent adversary behaviors. This development activity addresses two research components. First, establish an environment in which to perform the feasibility experiment and analysis. The proof of concept performed to analyze and assess this feasibility of utilizing an adversarial inferencing system to provide emergent adversary behavior is discussed. Second, determine if the appropriate interfaces can be reasonably established to provide integration with an existing force structure simulation framework. The authors also describe the envisioned simulation system and the software development performed to extend the inferencing engine and system interface toward that goal. The experimental results of observing emergent adversary behavior by applying the simulated COAs to the adversary model will be discussed. The research addresses numerous technological challenges in developing the necessary methodologies and tools for a software-based COA analysis framework utilizing intelligent adversarial intent.

Paper Details

Date Published: 4 September 2003
PDF: 8 pages
Proc. SPIE 5091, Enabling Technologies for Simulation Science VII, (4 September 2003); doi: 10.1117/12.501978
Show Author Affiliations
Joshua M. Surman, Air Force Research Lab. (United States)
Univ. at Buffalo (United States)
Robert G. Hillman, Air Force Research Lab. (United States)
Eugene Santos, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 5091:
Enabling Technologies for Simulation Science VII
Alex F. Sisti; Dawn A. Trevisani, Editor(s)

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